 ;; <br/>
 ;; # One last example showing everything together
 ;;
-;; Let's see how Semantic CSV in the context of a little data pipeline.
+;; Let's see how Semantic CSV works in the context of a little data pipeline.
 ;; We're going to thread data in, tranform into maps, run some computations for each row and assoc in,
 ;; then write the modified data out to a file, all lazily.
 ;; First let's show this with `clojure/data.csv`, which I find a little easier to use for writing.


(defn slurp-csv
  "This convenience function let's you `parse-and-process` csv data given a csv filename. Note that it is _not_
  lazy, and must read in all data so the file handle cna be closed."
  [csv-filename & {:as opts}]
  (let [rest-options (dissoc opts :parser-opts)]
    (with-open [in-file (io/reader csv-filename)]

;; For the ultimate in _programmer_ laziness:
;;
;;     (slurp-csv "test/test.csv"
;;                :cast-fns {:this #(Integer/parseInt %)})


;; <br/>
